Should I pursue an ML PhD for a future startup, or are university IP policies a dealbreaker?
I am a rising senior who has spent my undergrad preparing for a PhD, with the long-term goal of transitioning to industry and founding a startup (specifically focused on world models).
My main concern right now is Intellectual Property. I've read that if a company or product is tied to university research or resources, the institution can claim around 50%+ ownership. Giving up that much equity is a big concern for me.
I genuinely want to do a PhD for the learning experience and to build the credibility and technical foundation necessary to attract investors. I've worked hard to become a competitive applicant: a 3.9 GPA, multiple graduate courses, an NSF-funded REU, and two separate paid university research positions in math and CS. I also do not want to pay out of pocket for a Master's degree.
Because of my love for research, I kept pushing this IP conflict to the back burner. But now that I am at this point, I am wavering.
How restrictive are university IP policies in practice? Is there a way to safely pursue a PhD without compromising the IP of my future startup? Should I not pursue a PhD? Is Industry research an option even without a PhD? Any advice or shared experiences would be greatly appreciated.